Create app.py

app.py

@@ -9,19 +9,7 @@ from transformers import pipeline, AutoTokenizer
 from transformers import pipeline
 from pathlib import Path
 
-# load_model = AutoModelForSequenceClassification.from_pretrained("onnx")
- 
-# load_tokenizer = AutoTokenizer.from_pretrained("onnx")
-# st.write("Airi.uz jamoasi amaliyotchilari tomonidan tayyorlangan text classification uchun mo'ljallangan model")
-# st.write("Ishlatish uchun pastdagi maydonga matn kiriting va model sizga kiritilgan matnni qaysi sohaga aloqador ekanligini ko'rsatadi")
-# input = st.text_area(label='input_areaf',placeholder='matnni shu yerga kiriting',height=350,max_chars = 5000)
-# try:
-#       if st.button(label='bashorat qilish'):
-#             my_pipeline  = pipeline("text-classification", model=load_model, tokenizer=load_tokenizer)
-#             data = input
-#             st.info(my_pipeline(data))
-# except RuntimeError:
-#       st.info("Iltimos kamroq malumot kiriting")
+
 onnx_path = Path("onnx")
 model = ORTModelForSequenceClassification.from_pretrained(onnx_path, file_name="model_quantized.onnx")
 tokenizer = AutoTokenizer.from_pretrained(onnx_path)
@@ -35,9 +23,4 @@ try:
             data = input
             st.info(cls_pipeline(data))
 except RuntimeError:
-      st.info("Iltimos kamroq malumot kiriting")
-
-
-
-# results = cls_pipeline("Men rossiyaliklarga shuni aytmoqchimanki, butun sivilizatsiyalashgan dunyo biz terrorchi emasligimiz")
-# print(results)
+      st.info("Iltimos kamroq malumot kiriting")